Merge remote-tracking branch 'origin/main' into feature/solving-linear-systems-with-cuda

Author: chemardes

pdesolvers/main.py

@@ -16,14 +16,14 @@ def main():
     # solver2 = pde.Heat1DExplicitSolver(equation1)
 
     # testing for bse
-    equation2 = pde.BlackScholesEquation('call', 300, 1, 0.2, 0.05, 100, 10, 100)
+    equation2 = pde.BlackScholesEquation('call', 300, 1, 0.2, 0.05, 100, 100, 20000)
 
-    solver1 = pde.BlackScholesExplicitSolver(equation2)
+    solver1 = pde.BlackScholesCNSolver(equation2)
     res1 = solver1.solve()
     # res2 = solver2.solve()
 
     print(res1.get_result())
-    # res1.plot()
+    res1.plot()
 
 if __name__ == "__main__":
     main()

pdesolvers/solvers/black_scholes_solvers.py

@@ -1,5 +1,3 @@
-from operator import truediv
-
 from scipy import sparse
 from scipy.sparse.linalg import spsolve
 import numpy as np
@@ -85,9 +83,9 @@ def solve(self):
         dS = S[1] - S[0]
         dT = T[1] - T[0]
 
-        alpha = 0.25 * dT * ((self.equation.sigma**2) * (S**2) - self.equation.rate*S)
-        beta = -dT * 0.5 * (self.equation.sigma**2 * (S**2) + self.equation.rate)
-        gamma = 0.25 * dT * (self.equation.sigma**2 * (S**2) + self.equation.rate * S)
+        alpha = 0.25 * dT * ((self.equation.sigma**2) * (S**2) / (dS**2) - self.equation.rate * S / dS)
+        beta = -dT * 0.5 * (self.equation.sigma**2 * (S**2) / (dS**2) + self.equation.rate)
+        gamma = 0.25 * dT * (self.equation.sigma**2 * (S**2) / (dS**2) + self.equation.rate * S / dS)
 
         lhs = sparse.diags([-alpha[2:], 1-beta[1:], -gamma[1:-1]], [-1, 0, 1], shape = (self.equation.s_nodes - 1, self.equation.s_nodes - 1), format='csr')
         rhs = sparse.diags([alpha[2:], 1+beta[1:], gamma[1:-1]], [-1, 0, 1], shape = (self.equation.s_nodes - 1, self.equation.s_nodes - 1) , format='csr')